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Gene content characterization and genome organization of Corynebacterium
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pseudotuberculosis.
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Vivian D’Afonseca¹, Fernanda Alves Dorella¹, Luis Gustavo Pacheco¹, Pablo Matias
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Moraes¹, Francisco Prosdocimi², Izabella Pena², José Miguel Ortega², Santuza Teixeira3,
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Sérgio Costa Oliveira4, Guilherme Correa Oliveira5, Roberto Meyer6, Anderson
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Miyoshi¹**, Vasco Azevedo¹*
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1- Laboratório de Genética Celular e Molecular, Depto. Biologia Geral, ICB-UFMG
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2- Laboratório de Biodados, Depto. Bioquímica e Imunologia, ICB-UFMG
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3- Laboratório de Imunologia e Bioquímica Celular de Parasitas, Depto. Bioquímica e
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Imunologia, ICB-UFMG
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4- Laboratório de Imunologia de Doenças Infecciosas, Depto. Bioquímica e Imunologia,
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ICB-UFMG
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5- Laboratório de Parasitologia, Centro de Pequisa Reneé Rachou – Fiocruz
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6- Laboratório de Biointeração, Instituto de Ciências da Saúde, ICB - UFBA
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Vasco Azevedo* and Anderson Miyoshi** (shared credit in this work for senior
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authorship)
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vasco@icb.ufmg.br
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miyoshi@icb.ufmg.br
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Laboratório de Genética Celular e Molecular. Sala Q3-259.
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Departamento de Biologia Geral, ICB, UFMG
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Av. Antônio Carlos, 6627 C.P. 486
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31.270-010 Belo Horizonte, MG, Brazil
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Tel: +55 31 3499-2778
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Fax: +55 31 3499-2610
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Running Head
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Partial-identification of the gene content of C. pseudotuberculosis
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* To whom correspondence should be addressed
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Abbreviations: CLA, Caseous Lymphadenitis; GSS, Genome Survey Sequences; BLAST,
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Basic Local Alignment Search Tool; COG, Clusters of Orthologous Groups; Cd,
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Corynebacterium diphtheriae; Ce, Corynebacterium efficiens; Cg, Corynebacterium
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glutamicum; Cj, Corynebacterium jeikeium; Cp, Corynebacterium pseudotuberculosis.
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ABSTRACT
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Corynebacterium pseudotuberculosis is an intracellular pathogen that infects sheeps
and goats. The widespread occurrence of this pathogen and the economic
importance of the Caseous Lymphadenitis Disease (CLA) have prompted
investigation of its pathogenesis. However, the genetic basis of C.
pseudotuberculosis virulence is still poorly characterized. A genomic library
constructed from C. pseudotuberculosis was used for generation of Genomic
Survey Sequence (GSS). From both ends of 720 distinct clones were obtained 1440
GSS’s which were submitted to in silico analyses using bioinformatic algorithms
such as PHRED 0.16 base-caller, Seqclean and PHRAP (Crossmatch) package and
public databases to comparative analyses. These analyses resulted in about 1,000
GSS’s that presented lengths between 100 to 790 nucleotides and 346,860
basepairs. Non-redundants uniques sequences were used as query for BLAST
searches against the genome (BLASTn), translated genome (tBLASTx) and
proteome (BLASTx) of other four complete genome Corynebacterium species,
presenting more similarity to other Corynebacterium at protein level than at DNA
level. As results, we were able to characterize approximately 8% of the genome of
C. pseudotuberculosis, therefore, we characterize functional groups genes were
not described previously according to COG database, a closely relation between C.
pseudotuberculosis and C. diphteriae, beyond conserved genes sinteny in
Corynebacteria species.
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Keywords: Corynebacterium genus, Corynebacterium pseudotuberculosis, Genome
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Survey Sequences (GSS), microbial genome sequencing, partial-genome sequencing,
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comparative genomics.
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INTRODUCTION
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The decade 1990 was the starting point of the genomic era, with the
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sequencing of the first microbial genome, a free-living organism - the bacterium
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Haemophilus influenzae (Fleischmann et al., 1995; Mora et al., 2006). Since then,
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genomic researches allow to generate a lot of information that are available in public
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databases (Dorella et al., 2006a). These informations have been aid scientists
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discovery genes and its functionality, consequently proteins that its encoding,
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comparing genomes and species evolutionarily related (Celestino et al., 2004) and,
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although prokaryotic microorganisms occupy the largest part of the planet total
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biomass, (Rodrìguez-Valera, 2004), much more still need to be understood about
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them. Thus, the massive accumulation of prokaryotic DNA sequences generated by
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microbial genome projects can to provide greatest advances in our understanding in
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various fields including bacterial diversity, mobile genetic elements (MGE) and
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horizontal gene transfer (HGT) (Binnewies et al., 2006). Furthermore, genome
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sequencing has provided important insights on deduced genes and proteins of
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pathogens, including biological features, putative virulence factors and potential
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targets that might be useful for development of immunological or chemotherapeutic
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reagents against organism of choice (Celestino et al., 2004; Tauch et al., 2006). At
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present, around 570 microbial genome projects are finished and published, and more
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than 1100 are ongoing (Genomes OnLine Database, http://www.genomesonline.org/).
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The Corynebacterium genus consists of a large number of Gram-positive
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bacteria that are pleiomorphic, asporogenous and possess high G + C content in their
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genomes (Deb & Nath, 1999). Originally, the genus Corynebacterium had only
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diphtheria bacillus and some other animal-pathogenic species (Barksdale, 1970;
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Pascual, et al., 1995). Latest, other microorganisms were added including plant- and
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animal-pathogenic, nonpathogenic soil bacteria and saprophytic species (Collins &
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Bradbury, 1986; Collins & Cummins, 1986; Pascual, et al., 1995). Members of the
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genus Corynebacterium are closely related to Mycobacterium species, and both are
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classified into the taxonomic order Actinomycetales (Nakamura et al. 2003). At
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present, the National Center for Biotechnology Information (NCBI) genome database
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contains the complete genome of four different species from the Corynebacterium
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genus: Corynebacterium diphtheriae, Corynebacterium efficiens, Corynebacterium
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glutamicum and Corynebacterium jeikeium (Cerdeño-Tárraga et al., 2003; Ikeda et al.,
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2003; Nishio et al., 2003; Tauch et al., 2005).
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One of the most important members of this genus, and the focus of this paper,
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is the bacterium Corynebacterium pseudotuberculosis, a facultative intracellular
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pathogen that infects sheeps and goats, causing caseous lymphadenitis (CLA). This
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disease is worldwide spread, and its high economic importance has prompted
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investigation of its pathogenesis. However, the genetic determinants of C.
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pseudotuberculosis virulence are still poorly characterized (Dorella et al., 2006a),
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moreover, this specie presents only 19 proteins identified in GenPept database.
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In this context, the partial C. pseudotuberculosis genome sequence provided
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in this work may aid to improve the understanding about the molecular and genetic
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basis of this bacterium’s virulence, and still may be useful in the development of novel
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diagnostic methods, contributing to the control of CLA.
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METHODOLOGY
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Bacterial strains and growth conditions
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C. pseudotuberculosis wild-type strain T2 was isolated from a caseous
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granuloma found in a CLA-affected goat in Bahia state (Brazil) and identified by the
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API CORYNE battery (Biomerieux, France). This bacterium was aerobically grown in
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Brain Heart Infusion (BHI, Acumedia) broth at 37ºC under agitation (Dorella, 2006b).
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For attainment of recombinant clones we used the Escherichia coli DH5α strain,
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aerobically grown in Luria Bertani (LB, Difco Laboratories, Detroit, USA) and
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supplemented with ampicillin (100g/mL) and X-Gal (40g/mL) at 37ºC.
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Genomic DNA extraction and construction of genomic library
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Genomic DNA extraction was performed according to a previously described
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protocol (Pacheco et al, 2007). DNA integrity was confirmed through electrophoresis
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in 0.8% agarose gels and visualization by ethidium bromide staining. To evaluate the
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DNA clearly and quality we used spectrophotometer analysis. To obtain differently
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sized C. pseudotuberculosis DNA fragments, total genomic DNA was submitted to
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two minutes of nebulization (Roe et al, 1996). Fragmentation was confirmed through
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electrophoresis in 0.8% agarose gels and was obtained DNA fragments ranged from
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500 – 1000 pb. These fragments were cloned in PCR®4 Blunt-TOPO vector using
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TOPO® Shotgun Subcloning KIT (Invitrogen) and transformed into E. coli DH5α by
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electroporation (Dower et al, 1988).
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Blue-white screening was performed to select for positive clones, and PCR
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with M13 universal primers was used to confirm insert presence, according to the kit
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manufacturer’s instructions.
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GSS sequencing
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Plasmid extraction was performed directly on plates using a standardized
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protocol (Sambrook et al., 1989). Plasmids obtained were analyzed in 0.8% agarose
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gels and concentrations were determined spectrophotometrically.
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Obtained plasmidial DNA, around 200ng/µL, were submitted to sequencing
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reactions in a Mastercycler gradient (Eppendorf), using DYEnamic ET Dye
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Terminator Cycle Sequencing Kit (GE Healthcare) and universal primers M13 F and
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M13 R, following the manufacturer’s instructions. Sequences were generated in a
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MegaBACETM 1000 equipment (GE Healthcare).
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GSS amplification by PCR
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For confirmation of the presence of putative exclusives genes in
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Corynebacterium pseudotuberculosis and exclusion of any contamination were
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designed primers forward and reverse for each GSS which didn´t have similarities in
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the searches databases of the other sequenced Corynebacterium.
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Putative Oligopeptide/dipeptide ABC transporter primers:
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Forward: 5´-CCTTACCGAGACAACGTCAT-3´
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Reverse: 5´-GCCTGGTGCTTATCATTGAT-3´
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NADP oxidoreductase, coenzyme F420-dependent primers:
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Forward: 5´-CTGCGACATAGCTAGGCACT-3´
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Reverse: 5´-CCGCCAGACTTTTCTCTACA-3´
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Proline iminopeptidase (PIP) primers:
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Forward: 5´-AACTGCGGCTTTCTTTATTC-3´
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Reverse: 5´ -GACAAGTGGGAACGGTATCT-3´Generated amplicons presented
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lenght of: 285bp, 382bp and 551bp respectly.
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Base-calling
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The base-calling procedure was performed using PHRED algorithm (Ewing
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and Green, 1998; Ewing et al., 1998) with parameterization using trim_alt and
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trim_cutoff parameter of 0.16, as suggested by Prosdocimi and colleagues (2007).
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Sequence filtering and clustering
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In order to filter sequences from dust and vector sequences, we have used the
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algorithms SeqClean (http://compbio.dfci.harvard.edu/tgi/software/) and PHRAP’s
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package cross_match (http://www.phrap.org). SeqClean was firstly used to remove
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dust from PHRED base-called sequences. So, have been run cross_match algorithm
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against the sequence of cloning vector used in this analysis and, at least, SeqClean was
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once more run in order to remove the cross_match. The sequence clustering has been
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performed using TIGR software TGICL (Pertea et al., 2003) using default parameters.
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Comparative BLAST analyses against Corynebaterium complete genomes
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Non-redundant unique sequences clustered by TGICL were used as query to
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BLAST searches (Altschul et al., 1997) against other species from the
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Corynebacterium genus to identify similarities between these species and C.
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pseudotuberculosis uniques. We have run BLASTs in the DNA (BLASTn) and protein
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levels (BLASTx, tBLASTx) to verify the nucleotidic and amino acidic conservation
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among species.
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COG functional categories inference through Blast best hit analysis
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C. pseudotuberculosis unique sequences were also used as query to BLASTx
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searches against COG database (Tatusov et al., 1997). The NCBI COG database
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clusters genes from 66 microbial species into ortholog groups and classify these
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protein clusters into biological processes categories. A best hit inference approach
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method has been used to classify organism’s sequences into COG functional
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categories (REF). Therefore, BLASTx algorithm was run using 10e-5 e-value cut-off
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and C. pseudotuberculosis partial genome sequences were classified into COG
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categories based in the best hit match of each sequence against COG classified
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proteins.
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Comparative BLAST analyses against UNIPROT database
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The most recent version of UNIPROT curated protein database (Apweiler et
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al., 2004; Uniprot Consortium, 2007) was downloaded from EBI website at Feb 13,
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2007 (ftp://ftp.ebi.ac.uk/pub/ databases/uniprot/knowledgebase/uniprot_sprot.fasta.gz).
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Thus, it was used UNIPROT as database subject to BLASTx searches using C.
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pseudotuberculosis uniques as query. The number of protein hits was reported as well
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as the number of uniques matching UNIPROT proteins and not Corynebacterium
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genus or COG proteins.
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Gene synteny analysis with Corynebacterium genomes
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A synteny analysis of C. pseudotuberculosis non-redundant GSSs was also
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performed to verify if the gene order is conserved in C. pseudotuberculosis when
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compared to other Corynebacterium species. Using tBLASTx best hits data of C.
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pseudotuberculosis uniques against C. diphteriae, C. efficiens, C. glutamicum and C.
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jeikeium genomes, we have calculated the putative average position of each protein-
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coding gene (subject end minus subject init) when compared to other Corynebacterium
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complete genomes. The putative gene positional results were plotted in a graph
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ordered by C. diphteriae hits (C. pseudotuberculosis closest genome, see results).
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RESULTS
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Raw data filtering and processing
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The raw data produced by sequencer machines and base-calling was firstly
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filtered to remove vector regions and dust. Filtering has removed more than 30% of
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bases and sequences (Table 1). Moreover, larger sequences were diminished due to the
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presence of vector regions and/or dust contamination. Seqclean also removes from
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analysis all sequences smaller than 100 base pairs.
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Tab 1. Raw data analyses
RAW DATA
PROCESSED DATA
Number of sequences
1,440
963
Total number of residues
506,037
346,860
Smallest sequence
0
100
Largest sequence
906
792
Average length
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360
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Clustering Analysis
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C. pseudotuberculosis GSS have been clustered using TIGR’s TGICL
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software. This software uses Megablast (Zhang et al., 2000) to cluster sequences and
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CAP3 (Huang and Madan, 1999) to further assemble the sequences from each cluster.
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Such as expected, we have observed the presence of both many singlets and clusters
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presenting a small number of sequences, certifying the library quality (Figure 1). The
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non-redundant unique sequences have shown to span around 184,000 bases into 466
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non-redundant set of DNA sequences (Table 2).
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Fig1. Number of clusters by class of clustered sequences as defined by
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TGICL/Megablast.
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Tab 2. Clustering results
Number of
Number of
Average
Bigger
Smaller
bases
Sequences
Size (bp)
Sequence
Sequence
Singlets
91,047
276
331
792
100
Sequences clustered
255,813
687
372
786
100
Clusters
92,645
190
490
1248
121
183,692
466
395
1248
100
Sequence Class
GSS Uniques*
(non-redundant set)
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* Unique data (except bigger and smaller sequences) are a sum of singlets plus clusters
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data.
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BLAST against complete genome Corynebacterium species
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From the data above, all the analyses were made using the non-redundant set
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of C. pseudotuberculosis sequences (uniques). C. pseudotuberculosis GSS unique
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sequences were then used as query for BLAST searches against the genome
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(BLASTn), translated genome (tBLASTx) and proteome (BLASTx) of other complete
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genome Corynebacterium species (Table 3).
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Tab 3. BLAST analysis of C. pseudotuberculosis uniques against other
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Corynebacterium species.
BLAST
Subject
program
E-value
cutoff
cd*,a
ce*,a
cg*,a
cj*,a
tBLASTx
Genome
10-10
300 (100%)
244 (100%)
247 (100%)
198 (100%)
BLASTn
Genome
10-10
106 (35%)
42 (17%)
46 (19%)
31 (16%)
BLASTx
Proteome
10-10
268 (89%)
224 (92%)
221 (90%)
182 (92%)
BLASTx
Proteome
10-5
305
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275
235
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* Number of C. pseudotuberculosis uniques hitting other species’ genome;
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a
Percentage of search with Genome and tBLASTx
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It is interesting to realize that C. pseudotuberculosis has shown to be more
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similar to other Corynebaterium in the protein level than in the DNA level (Nakamura
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et al., 2003). Data on Table 3 suggests that C. pseudotuberculosis is more similar to
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C.diphteriae, followed by C. glutamicum, C. efficiens and C.jeikeium.
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Functional categorization of putative proteins based on best hits to COG database
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All GSS unique sequences were used as query to BLASTx searches against
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COG database. We have used 10-5 BLAST e-value cut-off and the C.
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pseudotuberculosis translated partial protein sequences were classified into functional
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categories based in the category of their best hit in COG database. Thus, C.
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pseudotuberculosis proteins were classified into major (Figure 2) and minor (Table 4)
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COG functional categories.
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Fig 2. GSS classification in major COG categories
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Almost half of C. pseudotuberculosis GSS uniques did not hit any protein in
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COG database, even with the low stringent BLAST cut-off used. Metabolism has
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shown to be the category on which most of genes were classified, while Information
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Storage and Processing, Cellular Processes and Poorly Characterized have shown to
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present a similar percentage of genes classified (~10%, Figure 2). Since these
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percentages do not mean too much without a comparative perspective, Table 4 present
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the expected percentage of genes classified in Corynebacterium, given by the COG
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classification of the four mentioned complete genome bacteria already sequenced from
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this genus.
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Table 4. COG functional classification of C. pseudotuberculosis putative partial
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proteins
COG Category
Cat*
Cp**
% in genus***
Inf
21 (4.2%)
3.9
(K) Transcription
Inf
23 (4.6%)
5.4
(L) DNA replication, recombination and repair
Inf
23 (4.6%)
5.2
(D) Cell division and chromosome partitioning
pCel
1 (0.2%)
0.5
pCel
8(1.6%)
2.2
(M) Cell envelope biogenesis, outer membrane
pCel
19 (3.8%)
3.1
(N) Cell motility and secretion
pCel
0
0.0
(U) Intracellular trafficking and secretion
pCel
1 (0.2%)
0.7
(V) Defense mechanisms
pCel
8 (1.6%)
1.3
(P) Inorganic ion transport and metabolism
pCel
21 (4.2%)
4.9
(T) Signal transduction mechanisms
pCel
11 (2.2%)
2.3
(C) Energy production and conversion
Met
14 (2.8%)
3.9
(H) Coenzyme metabolism
Met
19 (3.8%)
3.4
(I) Lipid metabolism
Met
14 (2.8%)
2.4
(G) Carbohydrate transport and metabolism
Met
21 (4.2%)
3.6
(E) Amino acid transport and metabolism
Met
28 (5.6%)
5.8
(F) Nucleotide transport and metabolism
Met
18 (3.6%)
2.1
Met
3 (0.6%)
1.7
(R) General function prediction only
Poor
29 (5.8%)
8.0
(S) Function unknown
Poor
17 (3.4%)
5.0
Not in COG
------
204 (40.6%)
33.3
(J)
Translation,
ribosomal
structure
and
biogenesis
(O)
Posttranslational
modification,
protein
turnover, chaperones
(Q)
Secondary
metabolites
biosynthesis,
transport and catabolism
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Cp: Corynebacterium pseudotuberculosis
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*Description of column data: Inf (information storage and processing), pCel (cellular
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processes), Met (metabolism), Poor (poorly characterized).
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**Number of genes found (and partial percentage) in cp genome. The absolute number
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is bigger than 514 since some genes were classified in more than one category.
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***Percentage
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(http://www.ncbi.nlm.nih.gov/sutils/coxik.cgi?gi=375)
in
genus
Corynebacterium
according
to
COG
data
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Most of GSS uniques classified data fits the expected percentage of
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classification into Corynebacterium genus if we consider this is only a partial analysis
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of C. pseudotuberculosis genome and proteome (Table 4). Confirming data on Figure
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2, we have seen an excess of sequences not classified.
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Shared hits against different databases
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In order to search for putative C. pseudotuberculosis genes originated by
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lateral transference, we have compared BLAST results against different databases. It
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would be expected that most of C. pseudotuberculosis genes derived from GSS will be
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present in other Corynebacterium species if they had been present in the common
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ancestor of all species inside this genus. This expectation has been confirmed (Figure
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3). However, we have observed the presence of 4 putative C. pseudotuberculosis
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proteins (translated uniques) presenting similarities with COG and UNIPROT proteins
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but not similarities with other Corynebacterium species proteins. Therefore, it is
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possible to consider these 4 proteins as putative candidates for lateral transference into
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C. pseudotuberculosis genome.
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Fig 3. Distribution of C. pseudotuberculosis GSS uniques’ BLAST hits against three
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databases tested: COG, UNIPROT and a built-in Corynebacterium protein database
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containing the proteomes
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These putative genes that might originated in C. pseudotuberculosis genome
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by lateral transference were identified as: (1) an oligopeptide/dipeptide ABC
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transporter, ATPase subunit with best hit in NR database against another bacteria
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(Arthrobacter sp. FB24) from the same order of C. pseudotuberculosis
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(Actinomycetales) (e-value 2e-19); (2) a NADP oxidoreductase, coenzyme F420-
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dependent from Chloroflexus aurantiacus, a bacterium of Chloroflexi phylum (e-value
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4e-10); (3) a proline iminopeptidase (PIP) from Xanthomonas axonopodis from
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Proteobacteria phylum (e-value 1e-55); and (4) a high-similarity (99% identities)
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complete sequence of a ribosomal protein L30 of the large (60S) ribosomal subunit
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from the baker yeast Saccharomyces cerevisiae (e-value 2e-61) (Figure 4).
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>gi|132946|sp|P24000|RL24B_YEAST Gene info 60S ribosomal protein L24-B (L30) (YL21) (RP29)
Length=155
Score = 238 bits (606), Expect = 2e-61
Identities = 154/155 (99%), Positives = 154/155 (99%), Gaps = 0/155 (0%)
Frame = -1
Query608 MKVEVDSFSGAKIYPGRGTLFVRGDSKIFRFQNSKSASLFKQRKNPRRIAWTVLFRKHHK 429
MKVEVDSFSGAKIYPGRGTLFVRGDSKIFRFQNSKSASLFKQRKNPRRIAWTVLFRKHHK
Sbjct 1
MKVEVDSFSGAKIYPGRGTLFVRGDSKIFRFQNSKSASLFKQRKNPRRIAWTVLFRKHHK 60
Query 428 KGITEEVAKKRSRKTVKAQRPITGASLDLIKERRSLKPEVRkanreeklkankekkraek 249
KGITEEVAKKRSRKTVKAQRPITGASLDLIKERRSLKPEVRKANREEKLKANKEKKRAEK
Sbjct 61
KGITEEVAKKRSRKTVKAQRPITGASLDLIKERRSLKPEVRKANREEKLKANKEKKRAEK 120
Query 248 aarkaekaKSAGVQGSKVSKQQAKGAFQKVAVTSR 144
AARKAEKAKSAGVQGSKVSKQQAKGAFQKVA TSR
Sbjct 121 AARKAEKAKSAGVQGSKVSKQQAKGAFQKVAATSR 155
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Fig 4. Best hit BLASTx result of a C. pseudotuberculosis unique against a complete
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sequence of a yeast 60S ribosomal protein. Putative case of lateral gene transfer to be
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further investigated.
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Confirmation of the putative genes of Corynebacterium pseudotuberculosis
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By PCR were confirmed the presence of 3 putative exclusives genes of
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Corynebacterium pseudotuberculosis. For this amplification, we used genomic DNA
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of the Corynebacterium pseudotuberculosis 1002 and T2 strain, Corynebacterium
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pseudotuberculosis equi, Corynebacterium ulcerans, Corynebacterium renale, which
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still didn´t have sequenced Corynebacterium diphteriae and Corynebacterium
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jeikeium. As negative control, was used vector TOPO only and positive control was
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the clone contained the fragment that originated the GSS (figure 5).
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408
A
409
M123456789
B
C
M1234 56 789
M123456789
382 bp
551 bp
285 bp
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Fig. 5: PCR confirmation of the presence of the putative genes in Corynebacterium
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pseudotuberculosis. (A) putative dipeptide/oligopeptide ABC transporter. (B) NADP
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oxirectudase. (C) PIP – proline iminopeptidase. (M) Molecular marker (1Kb Ladder
414
Plus); (1) Negative control; (2) Positive control; (3) C.pseudotuberculosis 1002; (4)
415
C.pseudotuberculosis T2; (5) C. renale; (6) C. ulcerans; (7) C.diphteriae; (8) C.
416
jeikeium; (9) C. pseudotuberculosis equi.
417
418
Gene order analysis
419
In order to verify whether the gene order is conserved in Corynebacterium
420
species, when compared to the C. pseudotuberculosis partial genome analysis done
421
here, we have used tBLASTx best hit results against C. diphteriae, C. glutamicum, C.
422
efficiens and C.jeikeium genomes to define the position where all the GSS C.
423
pseudotuberculosis putative genes have been mapped in those genomes.
17
424
425
Fig 6. Gene synteny analysis of C. pseudotuberculosis GSS uniques based in
426
tBLASTx genome mapping into other Corynebaterium genomes.
427
428
Therefore, all C. pseudotuberculosis GSS putative genes were mapped into
429
other Corynebacterium genomes (Figure 6) ordered by C. diphteriae genome. All
430
genomes have shown to present a high degree of gene order conservation when
431
compared to C. pseudotuberculosis mapped genes, while C.jeikeium has presented a
432
clear inversion in the very middle part of its genome when compared to others.
433
Moreover, triangles representing C. efficiens and C. glutamicum genomes can be seen
434
many times together, showing the similarity between these genomes. There were not
435
seen any squares representing the similarity of C. pseudotuberculosis genes with C.
436
diphteriae ones out of the main diagonal line, representing a putative high
437
conservation of gene order in these two species.
438
439
440
441
442
443
18
444
DISCUSSION
445
446
An overview from the C. pseudotuberculosis genome was done here based in
447
the sequence of ~1,000 genome survey sequences. The DNA clustering of these data
448
has shown to produce 466 sequences representing 183,692 base pair from this
449
organism genome. Other four Corynebacterium species from this same genus were
450
already sequenced and they present a genome size between 2.4 to 3.2 megabases
451
(Table 5).
452
453
Tab 5. Data from complete Corynebacterium genomes already sequenced
Genome
Number of
size (bp)
RefSeq proteins
NC_002935
2,488,635
2,291
ce
NC_004369
3,147,090
3,006
C. glutamicum
cg
NC_006958
3,282,708
3,057
C. jeikeium
cj
NC_007164
2,462,499
2,201
Organism
Mnemonic
Accession Number
C. diphteriae
cd
C. efficiens
454
455
Therefore, it might be concluded we have analyzed something between 5.6%
456
and 7.5% of C. pseudotuberculosis genome. Moreover, since C. pseudotuberculosis
457
has shown to be more similar in both the nucleotidic and the amino acid level to C.
458
diphteriae (Table 4), a species containing a 2.4 megabases genome, we have probably
459
analyzed here a number closer to 7.5% than 5.6% of C. pseudotuberculosis genome.
460
Many
similarity
analyses
were
performed
here
comparing
C.
461
pseudotuberculosis GSS genome data with the genome and proteome of other four
462
Corynebacterium species already sequenced. It is interesting to realize that better
463
similarity results were produced when the comparisons between these organisms were
464
done at the protein level. This may indicate they have already being evolutionary
465
diverged since a consider amount of time. Moreover, C. pseudotuberculosis has shown
466
to share more nucleotide and amino acid similarities against C. diphteriae than other
467
species (Table 4) as well as a similarity in their gene order (Figure 6). This observation
468
is consistent with sequencing data of 16S rRNA and rpoB genes, where these species
469
have clustered very close (Khamis et al., 2005). After C. diphteriae, C.
470
pseudotuberculosis has shown to present similar similarity levels against C. efficiens
471
and C. glutamicum; and more distant relationship with C. jeikeium genome. All these
19
472
data are consistent with the 16S rRNA and rpoB data produced by Khamis and
473
collaborators (2005) and summary presented in Figure 7.
474
475
476
Fig 7. Evolutionary relationship between Corynebaterium species studied here. This
477
data was derived from 16S rRNA and rpoB genes (Khamis et al., 2005) and it is in
478
accordance with similarity data shown here (Table 4).
479
The very high number of “no hits” seem in Figure 2 may be almost totally
480
explained looking into data in Table 5 and considering the size of non-coding regions
481
in Corynebacterium genomes. First, the last raw in Table 5 shows the number of genes
482
expected to be absent in COGs when some species from the Corynebacterium genus is
483
analyzed. Consequently, it is supposed that 33.3% of genes will not be classified in
484
COG categories in some species of Corynebacterium and C. pseudotuberculosis has
485
shown to present 40.6% of their non-redundant unique sequences classified in this
486
non-classified category. However, the number 33.3% in Table 5 is related only to the
487
percentage of genes not classified in COGs and the unique sequences represent both
488
genes and intergenic regions. When analyzing the Corynebacterium genomes trying to
489
find which part of them are composed of non-coding regions: C. diphteriae, C.
490
glutamicum, C. efficiens and C.jeikeium have shown present, respectively, 11.7%,
491
6.7%, 12.7% and 8.4% of their genomes composed of non protein-coding regions.
492
Therefore, if we consider an average putative value of 9.9% as C. pseudotuberculosis
493
genome non-coding region plus 33.3% of putative C. pseudotuberculosis proteins not
494
classified in COGs, we get a value of 43.2% of uniques expected to be not classified in
495
COGs and this number is close to the numbers seem in Figure 1 and Table 5 (40.6%).
496
Comparing the number of uniques presenting on BLAST hits into
497
Corynebacterium proteins but presenting significant similarities with proteins in
498
different curated protein databases (COG and UNIPROT), we have verified the
499
presence of some candidates C. pseudotuberculosis genes to be risen in this genome
500
through lateral gene transference. Amongst the 4 genes found in this category, a
501
proline iminopeptidase (PIP) and a ribosomal protein have shown high similarity
20
502
indexes with other species proteins. Regarding this ribosomal protein, we have found a
503
very high level identity in the entire sequence of an eukaryotic ribosomal protein from
504
S. cerevisiae (Figure 4). Presence of the 3 GSS were confirmed by PCR in C.
505
pseudotuberculosis (Figure 5), suggesting that PIP, putative oligopeptide/dipeptide
506
ABC transporter and NADP oxireductase actually are present into genome of C.
507
pseudotuberculosis, furthermore, it also is present in C. ulcerans (putative
508
dipeptide/oligopeptide ABC transporter), C. renale (all the 3 GSS) and didn´t present
509
in C. diphteriae and C. jeikeium as suggest our work. This gene presence in C.
510
pseudotuberculosis as well as C. renale and C. ulcerans was explained by Dorella and
511
colleagues, 2006 which based on analysis of the rpoB gene was suggested a clear
512
relationship between C. pseudotuberculosis and C. ulcerans.
513
The synteny of C. pseudotuberculosis putative genes and genes from other
514
Corynebacterium genomes were also evaluated in the present work (Figure 5). An
515
almost straight line can be seen when C. pseudotuberculosis putative gene positions
516
were mapped into C. diphteriae genome, evidencing the fact that our analysis has been
517
efficient in the sample of randomly disposed genes in the C. pseudotuberculosis
518
genome and once more attesting the quality of our genomic library. A broken line
519
would indicate that some regions had been preferentially sampled. Moreover, all the C.
520
pseudotuberculosis GSS uniques following the main diagonals in the Figure 5 are
521
suggested to be used as anchors to produce a final version of a further C.
522
pseudotuberculosis genome initiative. It is also interesting to observe that many C.
523
pseudotuberculosis genes were mapped in different positions when compared to C.
524
efficiens and C. glutamicum genomes. Nevertheless, in many situations it is possible to
525
see filled and not-filled triangles in similar positions (out of the diagonal), evidencing
526
also the similarity between C. efficiens and C. glutamicum genomes and their
527
differences when compared to C. diphteriae and C. pseudotuberculosis ones.
528
C.jeikeium genome has shown to be, such as expected, the most divergent species
529
when gene order is evaluated. Sinteny analysis suggests that Corynebacteria rarely
530
undergone genome rearrangements and have maintained ancestral genome structures
531
even after the divergence of Corynebacteria and Mycobacteria (Nakamura et al,
532
2003).
533
Thus, based on the analysis of ~1,000 C. pseudotuberculosis GSS sequences,
534
we have produced an overview of this bacterium genome. The sequence of ~8% of its
21
535
genome allowed us to confirm its evolutionary position among other complete genome
536
Corynebaterium and classify putative proteins into COG functional categories.
537
538
539
22
540
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